Robust Adaptive Actuator Failure Compensation for a Class of Uncertain Nonlinear Systems

This paper presents a robust adaptive state feedback control scheme for a class of parametric-strict-feedback nonlinear systems in the presence of time varying actuator failures. The designed adaptive controller compensates a general class of actuator failures without any need for explicit fault detection. The parameters, times, and patterns of the considered failures are completely unknown. The proposed controller is constructed based on a backstepping design method. The global boundedness of all the closed-loop signals is guaranteed and the tracking error is proved to converge to a small neighborhood of the origin. The proposed approach is employed for a two-axis positioning stage system as well as an aircraft wing system. The simulation results show the correctness and effectiveness of the proposed robust adaptive actuator failure compensation approach.

Adaptive sliding mode control of the A-axis used for blisk manufacturing

As a key assembly in the 5-axis CNC machine tools, positioning precision of the A-axis directly affects the machining accuracy and surface quality of the parts. First of all, mechanical structure and control system of the A-axis are designed. Then, considering the influence of nonlin- ear friction, backlash, unmodeled dynamics, uncertain cutting force and other external disturbance on the control precision of the A-axis, an adaptive sliding mode control （ASMC） based on extended state observer （ESO） is proposed. ESO is employed to estimate the state variables of the unknown system and an adaptive law is adopted to compensate for the input dead-zone caused by friction, backlash and other nonlinear characteristics. Finally, stability of the closed-loop system is guaran- teed by the Lyapunov theory. Positioning experiments illustrate the perfect estimation of ESO and the stronger anti-interference and robustness of ASMC, which can improve the control precision of the A-axis by about 40 times. Processing experiments show that the ASMC can reduce the waviness, averaKe error and roughness of the nrocessed surface by 35.63%, 31.31% and 30.35%, respectively.

Robust Control for Static Loading of Electro-hydraulic Load Simulator with Friction Compensation

Load simulator is a key test equipment for aircraft actuation systems in hardware-in-the-loop-simulation. Static loading is an essential function of the load simulator and widely used in the static/dynamic stiffness test of aircraft actuation systems. The tracking performance of the static loading is studied in this paper. Firstly, the nonlinear mathematical models of the hydraulic load simulator are derived, and the feedback linearization method is employed to construct a feed-forward controller to improve the force tracking performance. Considering the effect of the friction, a LuGre model based friction compensation is synthesized, in which the unmeasurable state is estimated by a dual state observer via a controlled learning mechanism to guarantee that the estimation is bounded. The modeling errors are attenuated by a well-designed robust controller with a control accuracy measured by a design parameter. Employing the dual state observer is to capture the different effects of the unmeasured state and hence can improve the friction compensation accuracy. The tracking performance is summarized by a derived theorem. Experimental results are also obtained to verify the high performance nature of the proposed control strategy.